Quantitative and rapid detection of nanoplastics labeled by luminescent metal phenolic networks using surface-enhanced Raman scattering

The escalating prevalence of nanoplastics contamination in environmental ecosystems has emerged as a significant health hazard. Conventional analytical methods are suboptimal, hindered by their inefficiency in analyzing nanoplastics at low concentrations and their time-intensive processes. In this context, we have developed an innovative approach that employs luminescent metal-phenolic networks (L-MPNs) coupled with surface-enhanced Raman spectroscopy (SERS) to separate and label nanoplastics, enabling rapid, sensitive and quantitative detection. Our strategy utilizes L-MPNs composed of zirconium ions, tannic acid, and rhodamine B to uniformly label nanoplastics across a spectrum of sizes (50-500 nm) and types (e.g., polystyrene, polymethyl methacrylate, polylactic acid). Rhodamine B (RhB) functions as a Raman reporter within these L-MPNs-based SERS tags, providing the requisite sensitivity for trace measurement of nanoplastics. Moreover, the labeling with L-MPNs aids in the efficient separation of nanoplastics from liquid media. Utilizing a portable Raman instrument, our methodology offers cost-effective, swift, and field-deployable detection capabilities, with excellent sensitivity in nanoplastic analysis and a detection threshold as low as 0.1 μg/mL. Overall, this study proposes a highly promising strategy for the robust and sensitive analysis of a broad spectrum of particle analytes, underscored by the effective labeling performance of L-MPNs when coupled with SERS techniques.

Evaluation of volume-based flow cytometry as a potential primary method for quantification of bacterial reference material

Bacterial reference materials (RMs) play a crucial role in many analytical processes of microbiological detection. Currently, bacteria are typically counted using the traditional plate-based approach, which results in a higher uncertainty of bacterial RMs unfortunately. Therefore, novel methods are urgently required for the value assignment of RMs in the field of microbiology to derive measurement traceability and accuracy. A potential primary method for microbiological quantification based on flow cytometry (FCM) is described in this study using Escherichia coli O157 (E. coli O157) as an example. The proposed method was applied to determine the number of viable E. coli O157 cells in the RMs with a result of (5.48 ± 0.27) × 10⁸ cells mL^-1, which was in good agreement with the result obtained using the plate-based method (E_n = 0.47). Additionally, this method could be entirely described and understood by equations, and provides formal traceability to the SI for counts of viable bacterial cells, while the associated relative expanded uncertainty (4.93%, k = 2) was significantly lower in comparison to the plate-based method. Therefore, the FCM-based method might be a potential primary method for characterizing bacterial RMs. To our knowledge, this is the first description of FCM as a potential primary method for accurate and traceable quantification of viable bacterial cells with a comprehensive uncertainty statement in microbiological metrology.

Improvement and application of qPCR assay revealed new insight on early warning of Phaeocystis globosa bloom

Phaeocystis globosa bloom develops from its early solitary cells, providing clues for early warning of its bloom and timely responding to possible consequences. However, the early prediction requires quantification of the solitary cells for a thorough understanding of bloom formation. Therefore, we developed an accurate, sensitive, and specific qPCR assay for this need. Results show that the accuracy of qPCR was significantly enhanced by ameliorating DNA barcode design, improving genomic DNA extraction, and introducing a strategy of internal amplification control (IAC). This approach reached a quantification limit of 1 cell/reaction, making low-abundance cells (10¹-10³ cells/L) detection possible, and we also observed a plunge in the abundance of the solitary cells before the bloom outbreak in two winters in 2019 and 2020 for the first time, which is quite unique from laboratory results showing an increase instead. The plunge in solitary-cell abundance might be associated with the attachment of solitary cells to solid matrices to form non-solitary attached aggregate, the precursor of colonies, which gains supports from other studies and needs more investigations in the future. Therefore, as the plunge in solitary-cell abundance is a sign of colony formation, it can be used as an early warning indicator to P. globosa bloom.

Comprehensive evaluation of chiral penflufen metabolite (penflufen-3-hydroxy-butyl): Identification, synthesis, enantioseparation, toxicity and enantioselective metabolism

Identification and evaluations of pesticide metabolites are necessary for risk assessment and toxicological research. In this study, the metabolites of penflufen (a widely used chiral pesticide) in rat liver microsomes were identified using liquid chromatography Q-Exactive Plus mass spectrometry. In total, 17 penflufen metabolites were identified, and most of them were hydroxylation products, which were generated by oxygenation at different candidate sites of penflufen. The relative abundance of metabolite M12 (penflufen-3-hydroxy-butyl, 32 %) was the largest, followed by M8 (15.6 %) and M2 (12.8 %). The major metabolite penflufen-3-hydroxy-butyl was first synthesized by 11 reactions with a 99.73 % purity. The absolute configuration of M12 enantiomers were confirmed after preparing enantiomers, and establishing the enantioseparation method. The M12 enantiomers toxicity to Danio rerio (LC₅₀, >10 mg/L) and four kinds of phytopathogens (EC₅₀, 148-34969 mg/L) were significantly lower than parents (LC₅₀, 0.449-24.3 mg/L; EC₅₀, 0.027-92.0 mg/L). In rat liver microsomes, approximately 40-47 % of the penflufen enantiomers were metabolized to M12 enantiomers, and R-penflufen was preferentially metabolized. The generation concentrations of S-M12 were higher than R-M12 after 10 min, and the metabolic half-lives of R-M12 (29.0-32.5 min) were shorter than S-M12 (35.2-38.1 min), and were approximately 4 times longer than parent penflufen enantiomers (4.5-9.5 min). Simultaneously, the generated contents (relative contents) of M8 (27.1-57 %) and M10 (2.22-8.36 %) from S-penflufen were lower than those from R-penflufen (M8, 24.7-92.4 %; M10, 27.4-69.5 %). The enantioselective evaluations of M12, M10 and M8 deserve further study. These findings were helpful in understanding the fate and risks of chiral penflufen.

Profiling of circRNAs using an enzyme-free digital counting method

Circular RNAs (circRNAs) have recently gained substantial attention as potential biomarkers in several human diseases, most prominently in cancer. However, the detection and quantification of circRNA biomarkers pose specific challenges owing to their circular nature. In particular, the use of enzymes, such as reverse transcriptases, may lead to impaired quantification, poor interlaboratory reproducibility and even false-positive results. Therefore, the development of methods for accurate quantification of circRNA biomarkers is a high priority. An enzyme-free and digital quantification method, named NanoString nCounter, was recently adapted for circRNA detection. In this review, I describe the advantages of using this technology for circRNA quantification as well as methodological considerations, potential pitfalls and disadvantages.

The importance of chromatographic resolution when analyzing steroid biomarkers

The analyses of endogenous substances as biomarkers presents challenges that are distinctly different from the analyses of drugs or other xenobiotic substances. This is particularly true for estrogens. When no matrix is available which does not contain some level of the biomarker of interest, specificity cannot be demonstrated. Therefore it cannot be known whether the analyte signal includes a response from another substance. This uncertainty is increased by the fact that biomarkers are often created as part of a complex biosynthetic process that also creates a large number of substances with very similar structures and sometimes the same mass. Because of this, the two most powerful selectivity tools in the analysis of drugs, mass selective detection and MS/MS, are often rendered ineffective. The only remaining selectivity tool is chromatography and as will be demonstrated these separations can be very challenging. Failure to achieve specificity is perhaps the leading cause for inaccuracy of biomarker data and inter-laboratory variability.